Full-Body Musculoskeletal Model for Muscle-Driven Simulation of Human Gait
Objective: Musculoskeletal models provide a noninvasive means to study human movement and predict the effects of interventions on gait. Our goal was to create an open-source 3-D musculoskeletal model with high-fidelity representations of the lower limb musculature of healthy young individuals that c...
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Published in | IEEE transactions on biomedical engineering Vol. 63; no. 10; pp. 2068 - 2079 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.10.2016
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Subjects | |
Online Access | Get full text |
ISSN | 0018-9294 1558-2531 1558-2531 |
DOI | 10.1109/TBME.2016.2586891 |
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Abstract | Objective: Musculoskeletal models provide a noninvasive means to study human movement and predict the effects of interventions on gait. Our goal was to create an open-source 3-D musculoskeletal model with high-fidelity representations of the lower limb musculature of healthy young individuals that can be used to generate accurate simulations of gait. Methods: Our model includes bony geometry for the full body, 37 degrees of freedom to define joint kinematics, Hill-type models of 80 muscle-tendon units actuating the lower limbs, and 17 ideal torque actuators driving the upper body. The model's musculotendon parameters are derived from previous anatomical measurements of 21 cadaver specimens and magnetic resonance images of 24 young healthy subjects. We tested the model by evaluating its computational time and accuracy of simulations of healthy walking and running. Results: Generating muscle-driven simulations of normal walking and running took approximately 10 minutes on a typical desktop computer. The differences between our muscle-generated and inverse dynamics joint moments were within 3% (RMSE) of the peak inverse dynamics joint moments in both walking and running, and our simulated muscle activity showed qualitative agreement with salient features from experimental electromyography data. Conclusion: These results suggest that our model is suitable for generating muscle-driven simulations of healthy gait. We encourage other researchers to further validate and apply the model to study other motions of the lower extremity. Significance: The model is implemented in the open-source software platform OpenSim. The model and data used to create and test the simulations are freely available at https://simtk.org/home/full_body/, allowing others to reproduce these results and create their own simulations. |
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AbstractList | Musculoskeletal models provide a non-invasive means to study human movement and predict the effects of interventions on gait. Our goal was to create an open-source 3-D musculoskeletal model with high-fidelity representations of the lower limb musculature of healthy young individuals that can be used to generate accurate simulations of gait.
Our model includes bony geometry for the full body, 37 degrees of freedom to define joint kinematics, Hill-type models of 80 muscle-tendon units actuating the lower limbs, and 17 ideal torque actuators driving the upper body. The model's musculotendon parameters are derived from previous anatomical measurements of 21 cadaver specimens and magnetic resonance images of 24 young healthy subjects. We tested the model by evaluating its computational time and accuracy of simulations of healthy walking and running.
Generating muscle-driven simulations of normal walking and running took approximately 10 minutes on a typical desktop computer. The differences between our muscle-generated and inverse dynamics joint moments were within 3% (RMSE) of the peak inverse dynamics joint moments in both walking and running, and our simulated muscle activity showed qualitative agreement with salient features from experimental electromyography data.
These results suggest that our model is suitable for generating muscle-driven simulations of healthy gait. We encourage other researchers to further validate and apply the model to study other motions of the lower extremity.
The model is implemented in the open-source software platform OpenSim. The model and data used to create and test the simulations are freely available at https://simtk.org/home/full_body/, allowing others to reproduce these results and create their own simulations. Musculoskeletal models provide a non-invasive means to study human movement and predict the effects of interventions on gait. Our goal was to create an open-source 3-D musculoskeletal model with high-fidelity representations of the lower limb musculature of healthy young individuals that can be used to generate accurate simulations of gait.OBJECTIVEMusculoskeletal models provide a non-invasive means to study human movement and predict the effects of interventions on gait. Our goal was to create an open-source 3-D musculoskeletal model with high-fidelity representations of the lower limb musculature of healthy young individuals that can be used to generate accurate simulations of gait.Our model includes bony geometry for the full body, 37 degrees of freedom to define joint kinematics, Hill-type models of 80 muscle-tendon units actuating the lower limbs, and 17 ideal torque actuators driving the upper body. The model's musculotendon parameters are derived from previous anatomical measurements of 21 cadaver specimens and magnetic resonance images of 24 young healthy subjects. We tested the model by evaluating its computational time and accuracy of simulations of healthy walking and running.METHODSOur model includes bony geometry for the full body, 37 degrees of freedom to define joint kinematics, Hill-type models of 80 muscle-tendon units actuating the lower limbs, and 17 ideal torque actuators driving the upper body. The model's musculotendon parameters are derived from previous anatomical measurements of 21 cadaver specimens and magnetic resonance images of 24 young healthy subjects. We tested the model by evaluating its computational time and accuracy of simulations of healthy walking and running.Generating muscle-driven simulations of normal walking and running took approximately 10 minutes on a typical desktop computer. The differences between our muscle-generated and inverse dynamics joint moments were within 3% (RMSE) of the peak inverse dynamics joint moments in both walking and running, and our simulated muscle activity showed qualitative agreement with salient features from experimental electromyography data.RESULTSGenerating muscle-driven simulations of normal walking and running took approximately 10 minutes on a typical desktop computer. The differences between our muscle-generated and inverse dynamics joint moments were within 3% (RMSE) of the peak inverse dynamics joint moments in both walking and running, and our simulated muscle activity showed qualitative agreement with salient features from experimental electromyography data.These results suggest that our model is suitable for generating muscle-driven simulations of healthy gait. We encourage other researchers to further validate and apply the model to study other motions of the lower extremity.CONCLUSIONThese results suggest that our model is suitable for generating muscle-driven simulations of healthy gait. We encourage other researchers to further validate and apply the model to study other motions of the lower extremity.The model is implemented in the open-source software platform OpenSim. The model and data used to create and test the simulations are freely available at https://simtk.org/home/full_body/, allowing others to reproduce these results and create their own simulations.SIGNIFICANCEThe model is implemented in the open-source software platform OpenSim. The model and data used to create and test the simulations are freely available at https://simtk.org/home/full_body/, allowing others to reproduce these results and create their own simulations. Objective: Musculoskeletal models provide a noninvasive means to study human movement and predict the effects of interventions on gait. Our goal was to create an open-source 3-D musculoskeletal model with high-fidelity representations of the lower limb musculature of healthy young individuals that can be used to generate accurate simulations of gait. Methods: Our model includes bony geometry for the full body, 37 degrees of freedom to define joint kinematics, Hill-type models of 80 muscle-tendon units actuating the lower limbs, and 17 ideal torque actuators driving the upper body. The model's musculotendon parameters are derived from previous anatomical measurements of 21 cadaver specimens and magnetic resonance images of 24 young healthy subjects. We tested the model by evaluating its computational time and accuracy of simulations of healthy walking and running. Results: Generating muscle-driven simulations of normal walking and running took approximately 10 minutes on a typical desktop computer. The differences between our muscle-generated and inverse dynamics joint moments were within 3% (RMSE) of the peak inverse dynamics joint moments in both walking and running, and our simulated muscle activity showed qualitative agreement with salient features from experimental electromyography data. Conclusion: These results suggest that our model is suitable for generating muscle-driven simulations of healthy gait. We encourage other researchers to further validate and apply the model to study other motions of the lower extremity. Significance: The model is implemented in the open-source software platform OpenSim. The model and data used to create and test the simulations are freely available at https://simtk.org/home/full_body/, allowing others to reproduce these results and create their own simulations. |
Author | Rajagopal, Apoorva Delp, Scott L. DeMers, Matthew S. Delp, Denny D. Dembia, Christopher L. Hicks, Jennifer L. |
Author_xml | – sequence: 1 givenname: Apoorva surname: Rajagopal fullname: Rajagopal, Apoorva organization: Department of Mechanical Engineering, Stanford University – sequence: 2 givenname: Christopher L. surname: Dembia fullname: Dembia, Christopher L. organization: Department of Mechanical Engineering, Stanford University – sequence: 3 givenname: Matthew S. surname: DeMers fullname: DeMers, Matthew S. organization: Department of Mechanical Engineering, Stanford University – sequence: 4 givenname: Denny D. orcidid: 0000-0001-6184-2728 surname: Delp fullname: Delp, Denny D. organization: Department of Mechanical Engineering, Stanford University – sequence: 5 givenname: Jennifer L. surname: Hicks fullname: Hicks, Jennifer L. organization: Department of Bioengineering, Stanford University – sequence: 6 givenname: Scott L. surname: Delp fullname: Delp, Scott L. email: delp@stanford.edu organization: Departments of Bioengineering and Mechanical Engineering, Stanford University, Stanford, CA, USA |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/27392337$$D View this record in MEDLINE/PubMed |
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CODEN | IEBEAX |
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Snippet | Objective: Musculoskeletal models provide a noninvasive means to study human movement and predict the effects of interventions on gait. Our goal was to create... Musculoskeletal models provide a non-invasive means to study human movement and predict the effects of interventions on gait. Our goal was to create an... |
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SubjectTerms | Biological system modeling Biomechanical Phenomena Biomechanics Biomedical Engineering Cadaver Computational modeling Computer Simulation Data models gait Gait - physiology Humans Male Models, Biological Muscle, Skeletal - physiology Muscles musculoskeletal model Pelvis running Running - physiology simulation Torque walking Walking - physiology Whole Body Imaging |
Title | Full-Body Musculoskeletal Model for Muscle-Driven Simulation of Human Gait |
URI | https://ieeexplore.ieee.org/document/7505900 https://www.ncbi.nlm.nih.gov/pubmed/27392337 https://www.proquest.com/docview/1823032465 https://pubmed.ncbi.nlm.nih.gov/PMC5507211 |
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